Publication Type : Journal Article
Thematic Areas : Center for Computational Engineering and Networking (CEN)
Publisher : International Journal of Applied Engineering Research
Source : International Journal of Applied Engineering Research, Volume 10, Issue 20, Number 20, p.19228-19233 (2015)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942847010&partnerID=40&md5=845226df63de9a3f3330a3dee4dd0ea0
Keywords : classification, Machine learning, Microsoft excel, Random kitchen sink (RKS), Regularized least square (RLS)
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Verified : Yes
Year : 2015
Abstract : In order to excavate on large chunks of unstructured data to retrieve the nuggets of knowledge, a lot of technically sound algorithms have been developed. In this paper, the classification of data has been performed in an efficient manner by inheriting concepts from linear algebra and optimization theory. This paper demonstrates the implementation of the mathematical ideas behind mapping input data to higher dimension using Random Kitchen Sink (RKS) and implementation of classification algorithm using Regularized Least Square (RLS) estimation. In this context, computational thinking methodology is accomplished using the most versatile tool available for non-programmers, that is excel. This paper elucidates a number of excel utilities. © Research India Publications.
Cite this Research Publication : Y. C. Nair, Binsha, P., V. Pradeep, V., Sowmya, and Dr. Soman K. P., “Spreadsheet implementation of random kitchen sink for classification”, International Journal of Applied Engineering Research, vol. 10, no. 20, pp. 19228-19233, 2015.